A PRN receiver such as a global positioning system receiver (GPS receiver) receives a PRN signal from a satellite to conduct range measurement. However, the GPS receiver receives both direct signals from the satellite as well as several multipath signals as a result of undesired reflections. The signal path of a reflected signal is longer than the signal path of a direct signal from the satellite. Such a reflected signal with a longer transmission path takes additional time to reach the receiver. Reflected signals also undergo attenuation and changes in polarization. These multiple signals, with varying phase and magnitude, result in a composite signal that does not accurately represent the true characteristics of the code and carrier phase of the direct signal.
The accuracy of the range measurements conducted by a GPS receiver depends upon the accuracy of alignment of the incoming direct signal from the satellite with the locally generated PRN signal of the GPS receiver. Multipath signals affect the accuracy of the estimated range. The combination of the direct signal and the multipath signals creates a composite signal. The receiver tracking loops align the locally generated code and carrier to the composite signal instead of the direct signal. The inaccuracy that results causes multipath errors in the range measurement conducted by the GPS receiver. The multipath errors manifest itself as a shift in the peak of the correlation function computed by the GPS receiver.
The PRN range, information is used to estimate the position, velocity and time of the user in a GPS system. The range information is derived from the satellite signals in the GPS Receiver. The incoming GPS signals undergo significant processing in the receiver for recovery of the GPS signal, differentiating it from the thermal noise. Current multipath mitigation solutions comprising signal processing algorithms in conjunction with suitable hardware are discussed below.
The methods of reducing multipath effects in a PRN ranging receiver can be broadly classified under antenna focused solutions, receiver hardware solutions, and signal and data processing solutions.
The antenna-based mitigation technique improves antenna gain pattern to counter the effects of multipath. This method includes the use of special antennas, spatial processing with multi-antenna arrays, antenna location strategies and long-term signal observation to infer multipath parameters, facilitated by changing reflection geometry.
Another approach uses a correlator with a fraction of code chip spacing and a large RF bandwidth. C/A codes are equally spaced with respect to the center correlator. Further, after the acquisition of a satellite, the correlators' spacing is static. Conventionally, the correlators are equally spaced with respect to each other. This approach is an effective solution for long delay multipath mitigation. It is the basis for the majority of the current high accuracy GPS receivers. However, this approach still does not eliminate a significant part of residual multipath errors.
Another approach involves the estimation of the slope of the two sides of the auto-correlation function in order to detect the auto-correlation peak. However, even this approach does not eliminate a significant part of residual multipath errors.
Another approach utilizes multiple narrowly-spaced correlators, generally in the order of ten or more correlators to estimate the entire correlation function. The method thereafter estimates various multipath parameters and computes the amount of multipath errors. However, this technique is most effective only when the physical multipath environment in which the antenna is located matches closely with the model used by the estimator in the receiver. Further, it requires very complex hardware to accomplish multipath mitigation.
Another approach of multipath mitigation uses a discriminator, wherein the discriminator is the difference of slopes of two sets of narrow correlators spaced at d chip and 2d chip spacing. This technique shows very good long delay multipath mitigation performance. It is not particularly effective for short delay multipath signals.
Yet another approach of multipath mitigation uses a cubic curve fit discriminant to determine the correlation function peak and a multipath indicator function to estimate the multipath error. However, this approach requires calibration of each GPS unit to characterize the RF front-end response. Further, it is most effective for reflected signals that have delays between 0.15Tc and 0.85Tc, where Tc represents the C/A (coarse acquisition) code chip width.
Several other researchers have devised methods to counter multipath effects using measurement data and other information generated by the receiver. These techniques and approaches are outside the scope of this invention.
In summary, the market requires a low cost multipath mitigation solution that accurately determines multipath errors, utilizing minimal hardware and requiring minimal calibration.